This section is intended to introduce various aspects of the art, which may be associated with exemplary embodiments of the present invention. This discussion is believed to assist in providing a framework to facilitate a better understanding of particular aspects of the present invention. Accordingly, it should be understood that this section should be read in this light, and not necessarily as admissions of prior art.
Seismic data is one of the most commonly used geophysical prospecting tools that is used to efficiently develop hydrocarbon reservoirs, which must be properly processed in order to allow interpretation of subsurface features including changes in fluid content or changes in pressure within a rock formation. Generally, seismic data is acquired by using active seismic sources to inject seismic energy into the subsurface which is then refracted or reflected by subsurface features and recorded at seismic receivers. For 4D seismic data, a first realization of the subsurface is acquired, usually pre-production, to obtain a ‘baseline’ seismic dataset and subsequent monitoring seismic surveys are acquired over the same subsurface formation to obtain one or more ‘monitor’ seismic dataset(s). In practice, seismic data is often contaminated by noise which may be coherent or incoherent (e.g. random) in nature. In 4D seismic comparisons, slight differences in survey parameters and/or processing can result in differences in amplitude and/or phase which may further contaminate the results.
4D seismic comparisons could be made by directly subtracting two seismic volumes, usually a baseline and a monitor, acquired at different points in time, usually months or years apart. This is referred to as the 4D seismic difference or 4D difference. What we observe in the 4D difference are generally attributed to changes in the reservoir, assuming, of course, that the monitor and baseline data sets have undergone a similar, if not identical, processing sequence and were carefully matched to compensate for differences in acquisition geometry, mechanical source and receiver signatures etc. Since the conventional subtraction method is a straight sample-by-sample subtraction of the two data sets, minor differences, especially in the phase or timing of the events, can cause large events in the output volume which can easily be mistaken for a 4D event. This often results in a ‘coherent’ seismic noise and primarily arises due to gap in coverage on one of the vintages, from acquisition, or residual statics differences between the vintages after processing. There can also be other type of specular or random noise on the 4D difference that usually impedes an interpreter from detecting or observing an actual 4D signal. This often results in an ‘incoherent’ seismic noise and is observed on a 4D difference volume after all processing, due to non-cancellation of migration swings, presence of residual multiples, swells, etc. between the vintages.
Efficient and effective methods for attenuating noise and isolating signal in seismic data are needed to improve the final seismic image and allow differentiating the 4D changes between the baseline and monitor seismic datasets. A methodology/workflow has been recently developed to remove migration swings, residual multiples and non-co located noise as observed on a 4D difference section. A 4D difference section between two vintages acquired over different periods of time over a producing reservoir tends to highlight changes due to production over the reservoir interval (rock property change due to change in pressure, fluid saturation etc.). If the acquisition and processing were ideal, then one would expect to see just this change due to physical properties over the reservoir interval. But differences in acquisition and processing tend to leave behind a lot of ‘4D noise’ that are not related to production. This 4D noise can be coherent or random in nature and can occur anywhere in the seismic data. The flowchart described in FIG. 1, referred to as the ‘curvelet4D’ workflow uses an initial realization between two datasets that were surveyed over the same subsurface location to come up with a common noise template and uses a Complex valued, Multi resolution, Directional Transform (CMDT), in particular a complex curvelet transform, to separate signal from noise. This process can be iterated multiple times until a pre-defined threshold based on a single or multiple 4D attributes is met.
U.S. Pat. No. 8,280,695, the entirety of which is hereby incorporated by reference, describes a method to adapt a template dataset to a target dataset by using curvelet representations. The template may be used to remove noise from, or interpret noise in, the target data set. The target data set is transformed using a selected complex-valued, directional, multi-resolution transform (‘CDMT’) satisfying the Hubert transform property at least approximately. An initial template is selected, and it is transformed using the same CDMT. Then the transformed template is adapted to the transformed target data by adjusting the template's expansion coefficients within allowed ranges of adjustment so as to better match the expansion coefficients of the target data set. Multiple templates may be simultaneously adapted to better fit the noise or other component of the data that it may be desired to represent by template.
U.S. Patent Publication 2013/0253838, the entirety of which is hereby incorporated by reference, describes a system and method for processing 4D seismic data. A system and method for determining a 4D difference from 4D seismic data includes receiving a baseline seismic dataset and a monitor seismic dataset; identifying a 4D signal present in the monitor seismic dataset to create a 4D monitor dataset and a signal in the baseline seismic dataset which matches the monitor seismic dataset to create a baseline matching signal dataset; differencing the baseline matching signal dataset and the baseline seismic dataset to create a 4D baseline dataset; and differencing the 4D baseline dataset and the 4D monitor dataset to create a 4D difference dataset. In an embodiment, a multi-scale, multi-directional transform is used to identify the 4D signal present in the monitor seismic dataset and the signal in the baseline seismic dataset which matches the monitor seismic dataset.
International Patent Publication WO 2015/036515, the entirety of which is hereby incorporated by reference, describes methods and apparatus for cooperative noise attenuation in data sets related to the same underground formation. Cooperative attenuation methods are applied to data sets acquired by surveying a same underground formation which therefore include substantially the same primary signal and different individual noise. The data sets are converted in a wavelet basis by applying a high angular resolution complex wavelet transform. When corresponding coefficients of the data set representations in the wavelet basis differ more than predefined thresholds the coefficients are attenuated as corresponding to noise.